Multivariate Methods > Latent Class Analysis
Publication date: 08/13/2020

Latent Class Analysis

Group Observations of Categorical Variables

Latent class analysis enables you to find clusters of observations for categorical response variables. A latent variable is an unobservable grouping variable. Each level of the latent variable is called a latent class. The Latent Class Analysis platform fits a latent class model and determines the most likely cluster or latent class for each observation. In most situations, a subject matter expert uses the results of a latent class analysis to create definitions for each latent class based on the characteristics of the class.

Figure 15.1 Example of Latent Class Analysis 

Contents

Overview of the Latent Class Analysis Platform

Example of Latent Class Analysis

Launch the Latent Class Analysis Platform

The Latent Class Analysis Report

Cluster Comparison Report
Latent Class Model Report

Latent Class Analysis Platform Options

Latent Class Analysis Options
Latent Class Model Options

Additional Example of the Latent Class Analysis Platform

Plot Probabilities of Cluster Membership

Statistical Details for the Latent Class Analysis Platform

Latent Class Model Fit
Maximum Number of Clusters
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